Theoretic basis and technical implementations of CT perfusion in acute ischemic stroke, part 1: Theoretic basis

Optimal Cerebral Blood Flow Thresholds for Ischemic Core Estimation Using Computed Tomography Perfusion and Diffusion-Weighted Imaging

OBJECTIVE

Computed tomography perfusion (CTP) imaging is crucial in quantifying cerebral blood flow (CBF) and thereby making an endovascular treatment (EVT) after large vessel occlusion. However, CTP is prone to overestimating the ischemic core. We sought to delineate the optimal regional CBF (rCBF) thresholds of pre-EVT CTP.

METHODS

We collected acute ischemic stroke patients due to large vessel occlusion who achieved successful recanalization with baseline CTP, immediate post-EVT diffusion-weighted image (DWI) within 3 hours, and delayed post-EVT DWI between 24 and 196 hours. Core volumes estimated by CTP at various rCBF thresholds were validated against immediate and delayed DWI lesion volumes.

RESULTS

A total of 175 acute large vessel occlusion patients were included. Baseline CTP was taken in a median of 24 minutes (interquartile range [IQR] 21-31 minutes) after arrival; after the CTP, groin puncture in a median of 37 minutes (IQR 28-52 minutes), immediate post-EVT DWI scans in a median of 1.6 hours (IQR 0.8-2.1 hours), and delayed DWI scans in a median of 89 hours (IQR 69-106 hours). The correlations between the rCBF thresholds were the best at rCBF <22% for immediate DWI (0.64; 95% CI 0.55-0.73) and at rCBF <30% for delayed DWI (0.69; 95% CI 0.61-0.76). The interval between CTP and recanalization was inversely correlated with the overestimation of ischemic core volume compared with the subsequent DWI.

INTERPRETATION

Optimal rCBF thresholds for estimating ischemic core using CTP depend significantly on the timing of DWI post-EVT and CTP to recanalization delay. The optimal rCBF thresholds for ischemic core estimation may vary depending on the clinical setting. ANN NEUROL 2025;97:919-929.

Development of a cerebral CT perfusion phantom: A structured approach

INTRODUCTION

Computed tomography perfusion (CTP) imaging is crucial in diagnosing and managing vascular diseases, e.g, stroke. Differences in scanners and protocols may lead to different results, affecting clinical decision-making. Objective validation and evaluation of CTP imaging are therefore important. Perfusion phantoms are essential test objects to facilitate the validation and evaluation of perfusion imaging. Therefore, this study aimed to develop, validate and evaluate a brain perfusion phantom for the evaluation of cerebral CTP.

METHODS

A cerebral perfusion phantom was developed to evaluate CTP imaging of the brain using a workflow based on the Design Science Research Methodology. The reliability and repeatability of the phantom's perfusion parameters derived from the time-density curves (TDCs) in CTP were evaluated.

RESULTS

A 3D-printed modular perfusion phantom was developed, filled with sodium alginate beads, and connected to a pumping system to mimic microvasculature and flow dynamics. The phantom consisted of three compartments that simulated different states of perfusion. The phantom showed reliable TDCs, with a relative standard deviation of <6.6 % for peak intensity and time-to-peak (TTP) over two sets of five repeated experiments for all compartments, and repeatable TTP and mean transit time values with a repeatability coefficient of <2.3 s compared to the mean.

CONCLUSIONS

The developed perfusion phantom demonstrated high reliability and could be employed for investigating CTP imaging under various flow speeds. The presented workflow promotes transparency in the development, validation, and application of CTP phantoms, and facilitates cross-study comparisons through structured iterative development and unified evaluation metrics.

Infarct core segmentation using U-Net in CT perfusion imaging: a feasibility study

BackgroundThe wide variability in thresholds on computed tomography (CT) perfusion parametric maps has led to controversy in the stroke imaging community about the most accurate measurement of core infarction.PurposeTo investigate the feasibility of using U-Net to perform infarct core segmentation in CT perfusion imaging.Material and MethodsCT perfusion parametric maps were the input of U-Net, while the ground truth segmentation was determined based on diffusion-weighted imaging (DWI). The dataset used in this study was from the ISLES2018 challenge, which contains 63 acute stroke patients receiving CT perfusion imaging and DWI within 8 h of stroke onset. The segmentation accuracy of model outputs was assessed by calculating Dice similarity coefficient (DSC), sensitivity, and intersection over union (IoU).ResultsThe highest DSC was observed in U-Net taking mean transit time (MTT) or time-to-maximum (Tmax) as input. Meanwhile, the highest sensitivity and IoU were observed in U-Net taking Tmax as input. A DSC in the range of 0.2-0.4 was found in U-Net taking Tmax as input when the infarct area contains < 1000 pixels. A DSC of 0.4-0.6 was found in U-Net taking Tmax as input when the infarct area contains 1000-1999 pixels. A DSC value of 0.6-0.8 was found in U-Net taking Tmax as input when the infarct area contains ≥ 2000 pixels.ConclusionOur model achieved good performance for infarct area containing ≥ 2000 pixels, so it may assist in identifying patients who are contraindicated for intravenous thrombolysis.

Is there a simple and accessible solution to improve acute infarct core imaging? The utility of steady-state CT angiographic source images obtained from a delayed phase acquisition

BACKGROUND

Early identification and quantification of core infarct is of importance in stroke management for treatment selection, prognostication, and complication prediction. Non-contrast computed tomography (CT) (NCCT) remains the primary tool, but it suffers from limited sensitivity and inter-rater variability; CT perfusion is inconsistently available and commonly blighted by movement artefact. We assessed the performance of a standardised form of CT angiographic source imaging (CTASI) obtained through addition of a delayed phase at 40 seconds post-contrast injection (DP40) following fast-acquisition CT angiography.

METHODS

Contrast resolution between ischaemic and normal grey matter (GM) was compared qualitatively and quantitatively to NCCT. Using Alberta Stroke Program Early CT Score (ASPECTS), DP40 low density was compared to NCCT and venous phase CT perfusion source images (CTPSI) and to 24-hour NCCT ASPECTS in patients with timely endovascular recanalisation (Thrombolysis In Cerebral Infarction 2C/3).

RESULTS

Seventy-four patients with a proximal middle cerebral artery or terminal internal carotid artery occlusion were included. The mean attenuation difference between ischaemic and normal GM increased from 4.86+/-3.12 HU (NCCT) to 9.30+/-3.14 HU (DP40) (p < 0.0001). Subjective assessment by two raters revealed that DP40 improved ischaemic tissue conspicuity in 39 to 41 (78-82%) of cases (kappa 0.805, standard error 0.108, 95% confidence interval: 0.593-1.000). The correlation between ASPECTS on baseline imaging and eventual 24-hour ASPECTS improved from R = 0.7197 for NCCT to R = 0.9875 for DP40 (z = 7.89, p < 0.0001). The correlation between DP40 and venous phase CTPSI ASPECTS was 0.9681, p < 0.0001.

CONCLUSION

DP40 CTASI represent a simple technique for improving detection and estimation of extent of ischaemia over NCCT and show close correlation with surrogate measures of infarct core.

Evaluating the effect of noise reduction strategies in CT perfusion imaging for predicting infarct core with deep learning

This study evaluates the efficacy of deep learning models in identifying infarct tissue on computed tomography perfusion (CTP) scans from patients with acute ischemic stroke due to large vessel occlusion, specifically addressing the potential influence of varying noise reduction techniques implemented by different vendors. We analyzed CTP scans from 60 patients who underwent mechanical thrombectomy achieving a modified thrombolysis in cerebral infarction (mTICI) score of 2c or 3, ensuring minimal changes in the infarct core between the initial CTP and follow-up MR imaging. Noise reduction techniques, including principal component analysis (PCA), wavelet, non-local means (NLM), and a no denoising approach, were employed to create hemodynamic parameter maps. Infarct regions identified on follow-up diffusion-weighted imaging (DWI) within 48 hours were co-registered with initial CTP scans and refined with ADC maps to serve as ground truth for training a data-augmented U-Net model. The performance of this convolutional neural network (CNN) was assessed using Dice coefficients across different denoising methods and infarct sizes, visualized through box plots for each parameter map. Our findings show no significant differences in model accuracy between PCA and other denoising methods, with minimal variation in Dice scores across techniques. This study confirms that CNNs are adaptable and capable of handling diverse processing schemas, indicating their potential to streamline diagnostic processes and effectively manage CTP input data quality variations.

Deep learning biomarker of chronometric and biological ischemic stroke lesion age from unenhanced CT

Estimating progression of acute ischemic brain lesions - or biological lesion age - holds huge practical importance for hyperacute stroke management. The current best method for determining lesion age from non-contrast computerised tomography (NCCT), measures Relative Intensity (RI), termed Net Water Uptake (NWU). We optimised lesion age estimation from NCCT using a convolutional neural network - radiomics (CNN-R) model trained upon chronometric lesion age (Onset Time to Scan: OTS), while validating against chronometric and biological lesion age in external datasets (N = 1945). Coefficients of determination (R2) for OTS prediction, using CNN-R, and RI models were 0.58 and 0.32 respectively; while CNN-R estimated OTS showed stronger associations with ischemic core:penumbra ratio, than RI and chronometric, OTS (ρ2 = 0.37, 0.19, 0.11); and with early lesion expansion (regression coefficients >2x for CNN-R versus others) (all comparisons: p < 0.05). Concluding, deep-learning analytics of NCCT lesions is approximately twice as accurate as NWU for estimating chronometric and biological lesion ages.

Comparison of Perfusion Imaging Definitions of the No-Reflow Phenomenon after Thrombectomy-What Is the Best Perfusion Imaging Definition?

The no-reflow phenomenon is a potential contributor to poor outcome despite successful thrombectomy. There are multiple proposed imaging-based definitions of no-reflow leading to wide variations in reported prevalence. We investigated the agreement between existing imaging definitions and compared the characteristics and outcomes of patients identified as having no-reflow.

METHODS

We performed an external validation of 4 existing published definitions of no-reflow in thrombectomy patients with extended Thrombolysis in Cerebral Infarction scale 2c to 3 (eTICI2c-3) angiographic reperfusion who underwent 24-hour perfusion imaging from 2 international randomized controlled trials (EXTEND-IA TNK part-1 and 2) and a multicenter prospective observational study. Receiver-operating-characteristic and Bayesian-information-criterion (BIC) analyses were performed with the outcome variable being dependent-or-dead at 90-days (modified Rankin Score [mRS] ≥3).

RESULTS

Of 131 patients analyzed, the prevalence of no-reflow significantly varied between definitions (0.8-22.1%; p < 0.001). There was poor agreement between definitions (kappa 5/6 comparisons <0.212). Among patients with no-reflow according to at least 1 definition, there were significant differences between definitions in the intralesional interside differences in cerebral blood flow (CBF) (p = 0.006), cerebral blood volume (CBV) (p < 0.001), and mean-transit-time (MTT) (p = 0.005). No-reflow defined by 3 definitions was associated with mRS ≥3 at 90 days. The definition of >15% CBV or CBF asymmetry was the only definition that improved model fit on BIC analysis (ΔBIC = -8.105) and demonstrated an association between no-reflow and clinical outcome among patients with eTICI3 reperfusion.

CONCLUSIONS

Existing imaging definitions of no-reflow varied significantly in prevalence and post-treatment perfusion imaging profile, potentially explaining the variable prevalence of no-reflow reported in literature. The definition of >15% CBV or CBF asymmetry best discriminated for functional outcome at 90 days, including patients with eTICI3 reperfusion. ANN NEUROL 2024;96:1104-1114.

Pretreatment Cranial Computed Tomography Perfusion Predicts Dynamic Cerebral Autoregulation Changes in Acute Hemispheric Stroke Patients Having Undergone Recanalizing Therapy: A Retrospective Study

OBJECTIVES

Blood pressure (BP) management is challenging in patients with acute ischemic supratentorial stroke undergoing recanalization therapy due to the lack of established guidelines. Assessing dynamic cerebral autoregulation (dCA) may address this need, as it is a bedside technique that evaluates the transfer function phase in the very low-frequency (VLF) range (0.02-0.07 Hz) between BP and cerebral blood flow velocity (CBFV) in the middle cerebral artery. This phase is a prognostically relevant parameter, with lower values associated with poorer outcomes. This study aimed to evaluate whether early cranial computed tomography perfusion (CTP) can predict this parameter.

METHODS

In this retrospective study, 165 consecutive patients with hemispheric strokes who underwent recanalizing therapy were included (median age: 73 years; interquartile range (IQR) 60-80; women: 43 (26%)). The cohort comprised 91 patients treated with intravenous thrombolysis (IV-lysis) alone (median National Institute of Health Stroke Scale (NIHSS) score: 5; IQR 3-7) and 74 patients treated with mechanical thrombectomy (median NIHSS: 15; IQR 9-18). Regression analysis was performed to assess the relationship between pretreatment CTP-derived ischemic penumbra and core stroke volumes and the dCA VLF phase, as well as CBFV assessed within the first 72 h post-stroke event.

RESULTS

Pretreatment penumbra volume was a significant predictor of the VLF phase (adjusted r2 = 0.040; β = -0.001, 95% confidence interval (CI): -0.0018 to -0.0002, p = 0.02). Core infarct volume was a stronger predictor of CBFV (adjusted r2 = 0.082; β = 0.205, 95% CI: 0.0968-0.3198; p = 0.0003) compared to penumbra volume (p = 0.01). Additionally, in the low-frequency range (0.07-0.20 Hz), CBFV and BP were inversely related to the gain, an index of vascular tone.

CONCLUSION

CTP metrics appear to correlate with the outcome-relevant VLF phase and reactive hyperemic CBFV, which interact with BP to influence vascular tone and gain. These aspects of dCA could potentially guide BP management in patients with acute stroke undergoing recanalization therapy. However, further validation is required.

CT perfusion imaging in aneurysmal subarachnoid hemorrhage. State of the art

CT perfusion (CTP) images can be easily and rapidly obtained on all modern CT scanners and have become part of the routine imaging protocol of patients with aneurysmal subarachnoid haemorrhage (aSAH). There is a growing body of evidence supporting the use of CTP imaging in these patients, however, there are significant differences in the software packages and methods of analysing CTP. In. addition, no quantitative threshold values for tissue at risk (TAR) have been validated in this patients' population. Here we discuss the contribution of the technique in the identification of patients at risk of aSAH-related delayed cerebral ischemia (DCI) and in the assessment of the response to endovascular rescue therapy (ERT). We also address the limitations and pitfalls of automated CTP postprocessing that are specific to aSAH patients as compared to acute ischemic stroke (AIS).

A clinical and computed tomography-based nomogram to predict the outcome in patients with anterior circulation large vessel occlusion after endovascular mechanical thrombectomy

PURPOSE

To explore the positive predictors of the clinical outcome in acute ischemic stroke (AIS) patients with anterior circulation large vessel occlusion (ACLVO) after endovascular mechanical thrombectomy (EMT) at a 90-day follow-up, and to establish a nomogram model to predict the clinical outcome.

MATERIALS AND METHODS

AIS patients with ACLVO detected by multimodal Computed Tomography imaging who underwent EMT were collected. Patients were divided into the favorable and the unfavorable groups according to the 90-day modified Rankin Scale (mRS) score. Univariate and multivariate analyses were performed to investigate predictors of the favorable outcome (mRS of 0-2). A nomogram model for predicting the clinical outcome after EMT was drawn, and the receiver operating characteristic (ROC) curve was used to evaluate its predictive value.

RESULTS

Totally 105 patients including 65 patients in the favorable group and 40 in the unfavorable group were enrolled. Multivariate logistic regression analysis showed that admission National Institute of Health Stroke scale (NIHSS) score [0.858 (95% CI 0.778-0.947)], ACLVO at M2 [20.023 (95% CI 2.204-181.907)] and infarct core (IC) volume [0.943 (95% CI 0.917-0.969)] was positively correlated with favorable outcome. The accuracy of the nomogram model in predicting the outcome was 0.923 (95% CI 0.870-0.976), with a cutoff value of 119.6 points. The area under the ROC curve was 0.848 (95% CI 0.780-0.917; sensitivity, 79.7%; specificity, 90.0%).

CONCLUSION

A low Admission NIHSS score, ACLVO at M2, and a small IC volume were positive predictors for favorable outcome. The nomogram model may well predict the outcome in AIS patients with ACLVO after EMT.

Turn-table micro-CT scanner for dynamic perfusion imaging in mice: design, implementation, and evaluation

Objective.This study introduces a novel desktop micro-CT scanner designed for dynamic perfusion imaging in mice, aimed at enhancing preclinical imaging capabilities with high resolution and low radiation doses.Approach.The micro-CT system features a custom-built rotating table capable of both circular and helical scans, enabled by a small-bore slip ring for continuous rotation. Images were reconstructed with a temporal resolution of 3.125 s and an isotropic voxel size of 65µm, with potential for higher resolution scanning. The system's static performance was validated using standard quality assurance phantoms. Dynamic performance was assessed with a custom 3D-bioprinted tissue-mimetic phantom simulating single-compartment vascular flow. Flow measurements ranged from 1.51to 9 ml min-1, with perfusion metrics such as time-to-peak, mean transit time, and blood flow index calculated.In vivoexperiments involved mice with different genetic risk factors for Alzheimer's and cardiovascular diseases to showcase the system's capabilities for perfusion imaging.Main Results.The static performance validation confirmed that the system meets standard quality metrics, such as spatial resolution and uniformity. The dynamic evaluation with the 3D-bioprinted phantom demonstrated linearity in hemodynamic flow measurements and effective quantification of perfusion metrics.In vivoexperiments highlighted the system's potential to capture detailed perfusion maps of the brain, lungs, and kidneys. The observed differences in perfusion characteristics between genotypic mice illustrated the system's capability to detect physiological variations, though the small sample size precludes definitive conclusions.Significance.The turn-table micro-CT system represents a significant advancement in preclinical imaging, providing high-resolution, low-dose dynamic imaging for a range of biological and medical research applications. Future work will focus on improving temporal resolution, expanding spectral capabilities, and integrating deep learning techniques for enhanced image reconstruction and analysis.

Multicenter comparison using two AI stroke CT perfusion software packages for determining thrombectomy eligibility

BACKGROUND

Stroke AI platforms assess infarcted core and potentially salvageable tissue (penumbra) to identify patients suitable for mechanical thrombectomy. Few studies have compared outputs of these platforms, and none have been multicenter or considered NIHSS or scanner/protocol differences. Our objective was to compare volume estimates and thrombectomy eligibility from two widely used CT perfusion (CTP) packages, Viz.ai and RAPID.AI, in a large multicenter cohort.

METHODS

We analyzed CTP data of acute stroke patients with large vessel occlusion (LVO) from four institutions. Core and penumbra volumes were estimated by each software and DEFUSE-3 thrombectomy eligibility assessed. Results between software packages were compared and categorized by NIHSS score, scanner manufacturer/model, and institution.

RESULTS

Primary analysis of 362 cases found statistically significant differences in both software's volume estimations, with subgroup analysis showing these differences were driven by results from a single scanner model, the Canon Aquilion One. Viz.ai provided larger estimates with mean differences of 8cc and 18cc for core and penumbra, respectively (p<0.001). NIHSS subgroup analysis also showed systematically larger Viz.ai volumes (p<0.001). Despite volume differences, a significant difference in thrombectomy eligibility was not found. Additional subgroup analysis showed significant differences in penumbra volume for the Phillips Ingenuity scanner, and thrombectomy eligibility for the Canon Aquilion One scanner at one center (7 % increased eligibility with Viz.ai, p=0.03).

CONCLUSIONS

Despite systematic differences in core and penumbra volume estimates between Viz.ai and RAPID.AI, DEFUSE-3 eligibility was not statistically different in primary or NIHSS subgroup analysis. A DEFUSE-3 eligibility difference, however, was seen on one scanner at one institution, suggesting scanner model and local CTP protocols can influence performance and cause discrepancies in thrombectomy eligibility. We thus recommend centers discuss optimal scanning protocols with software vendors and scanner manufacturers to maximize CTP accuracy.

Deep Learning for Perfusion Cerebral Blood Flow (CBF) and Volume (CBV) Predictions and Diagnostics

Dynamic susceptibility contrast magnetic resonance perfusion (DSC-MRP) is a non-invasive imaging technique for hemodynamic measurements. Various perfusion parameters, such as cerebral blood volume (CBV) and cerebral blood flow (CBF), can be derived from DSC-MRP, hence this non-invasive imaging protocol is widely used clinically for the diagnosis and assessment of intracranial pathologies. Currently, most institutions use commercially available software to compute the perfusion parametric maps. However, these conventional methods often have limitations, such as being time-consuming and sensitive to user input, which can lead to inconsistent results; this highlights the need for a more robust and efficient approach like deep learning. Using the relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) perfusion maps generated by FDA-approved software, we trained a multistage deep learning model. The model, featuring a combination of a 1D convolutional neural network (CNN) and a 2D U-Net encoder-decoder network, processes each 4D MRP dataset by integrating temporal and spatial features of the brain for voxel-wise perfusion parameters prediction. An auxiliary model, with similar architecture, but trained with truncated datasets that had fewer time-points, was designed to explore the contribution of temporal features. Both qualitatively and quantitatively evaluated, deep learning-generated rCBV and rCBF maps showcased effective integration of temporal and spatial data, producing comprehensive predictions for the entire brain volume. Our deep learning model provides a robust and efficient approach for calculating perfusion parameters, demonstrating comparable performance to FDA-approved commercial software, and potentially mitigating the challenges inherent to traditional techniques.

Review of Cerebral Collateral Circulation and Insight into Cardiovascular Strategies to Limit Collateral Damage in Ischemic Stroke

Cerebral collateral circulation is a dynamic and adaptive process by which alternative vascular pathways supply perfusion to ischemic brain tissue in the event of an arterial occlusion. This complicated network of blood vessels that acts as a natural bypass plays a pivotal role in stroke pathophysiology and has become a key area of study given its significance in stroke treatment and patient outcomes. In this review, we will study the factors influencing the formation, recruitment, and endurance of collateral vessels; discuss imaging modalities for quantitative and qualitative assessment of this network; explore the role of collaterals in stroke management; and highlight several cardiovascular strategies to minimize damage to collaterals and optimize stroke outcomes.

CT Perfusion Map Synthesis from CTP Dynamic Images Using a Learned LSTM Generative Adversarial Network for Acute Ischemic Stroke Assessment

Computed tomography perfusion (CTP) is a dynamic 4-dimensional imaging technique (3-dimensional volumes captured over approximately 1 min) in which cerebral blood flow is quantified by tracking the passage of a bolus of intravenous contrast with serial imaging of the brain. To diagnose and assess acute ischemic stroke, the standard method relies on summarizing acquired CTPs over the time axis to create maps that show different hemodynamic parameters, such as the timing of the bolus arrival and passage (Tmax and MTT), cerebral blood flow (CBF), and cerebral blood volume (CBV). However, producing accurate CTP maps requires the selection of an arterial input function (AIF), i.e. a time-concentration curve in one of the large feeding arteries of the brain, which is a highly error-prone procedure. Moreover, during approximately one minute of CT scanning, the brain is exposed to ionizing radiation that can alter tissue composition, and create free radicals that increase the risk of cancer. This paper proposes a novel end-to-end deep neural network that synthesizes CTP images to generate CTP maps using a learned LSTM Generative Adversarial Network (LSTM-GAN). Our proposed method can improve the precision and generalizability of CTP map extraction by eliminating the error-prone and expert-dependent AIF selection step. Further, our LSTM-GAN does not require the entire CTP time series and can produce CTP maps with a reduced number of time points. By reducing the scanning sequence from about 40 to 9 time points, the proposed method has the potential to minimize scanning time thereby reducing patient exposure to CT radiation. Our evaluations using the ISLES 2018 challenge dataset consisting of 63 patients showed that our model can generate CTP maps by using only 9 snapshots, without AIF selection, with an accuracy of 84.37 % .

Reducing False-Positives in CT Perfusion Infarct Core Segmentation Using Contralateral Local Normalization

BACKGROUND AND PURPOSE

The established global threshold of rCBF <30% for infarct core segmentation can lead to false-positives, as it does not account for the differences in blood flow between GM and WM and patient-individual factors, such as microangiopathy. To mitigate this problem, we suggest normalizing each voxel not only with a global reference value (ie, the median value of normally perfused tissue) but also with its local contralateral counterpart.

MATERIALS AND METHODS

We retrospectively enrolled 2830 CTP scans with suspected ischemic stroke, of which 335 showed obvious signs of microangiopathy. In addition to the conventional, global normalization, a local normalization was performed by dividing the rCBF maps with their mirrored and smoothed counterpart, which sets each voxel value in relation to the contralateral counterpart, intrinsically accounting for GM and WM differences and symmetric patient individual microangiopathy. Maps were visually assessed and core volumes were calculated for both methods.

RESULTS

Cases with obvious microangiopathy showed a strong reduction in false-positives by using local normalization (mean 14.7 mL versus mean 3.7 mL in cases with and without microangiopathy). On average, core volumes were slightly smaller, indicating an improved segmentation that was more robust against naturally low blood flow values in the deep WM.

CONCLUSIONS

The proposed method of local normalization can reduce overestimation of the infarct core, especially in the deep WM and in cases with obvious microangiopathy. False-positives in CTP infarct core segmentation might lead to less-than-optimal therapy decisions when not correctly interpreted. The proposed method might help mitigate this problem.

Synthetic interpolated DSA for radiation exposure reduction via gamma variate contrast flow modeling: a retrospective cohort study

BACKGROUND

Digital subtraction angiography (DSA) yields high cumulative radiation dosages (RD) delivered to patients. We present a temporal interpolation of low frame rate angiograms as a method to reduce cumulative RDs.

METHODS

Patients undergoing interventional evaluation and treatment of cerebrovascular vasospasm following subarachnoid hemorrhage were retrospectively identified. DSAs containing pre- and post-intervention runs capturing the full arterial, capillary, and venous phases with at least 16 frames each were selected. Frame rate reduction (FRR) of the original DSAs was performed to 50%, 66%, and 75% of the original frame rate. Missing frames were regenerated by sampling a gamma variate model (GVM) fit to the contrast response curves to the reduced data. A formal reader study was performed to assess the diagnostic accuracy of the "synthetic" studies (sDSA) compared to the original DSA.

RESULTS

Thirty-eight studies met inclusion criteria (average RD 1,361.9 mGy). Seven were excluded for differing views, magnifications, or motion. GVMs fit to 50%, 66%, and 75% FRR studies demonstrated average voxel errors of 2.0 ± 2.5% (mean ± standard deviation), 6.5 ± 1.5%, and 27 ± 2%, respectively for anteroposterior projections, 2.0 ± 2.2%, 15.0 ± 3.1%, and 14.8 ± 13.0% for lateral projections, respectively. Reconstructions took 0.51 s/study. Reader studies demonstrated an average rating of 12.8 (95% CI 12.3-13.3) for 75% FRR, 12.7 (12.2-13.2) for 66% FRR and 12.0 (11.5-12.5) for 50% FRR using Subjective Image Grading Scale. Kendall's coefficient of concordance resulted in W = 0.506.

CONCLUSION

FRR by 75% combined with GVM reconstruction does not compromise diagnostic quality for the assessment of cerebral vasculature.

RELEVANCE STATEMENT

Using this novel algorithm, it is possible to reduce the frame rate of DSA by as much as 75%, with a proportional reduction in radiation exposure, without degrading imaging quality.

KEY POINTS

• DSA delivers some of the highest doses of radiation to patients. • Frame rate reduction (FRR) was combined with bolus tracking to interpolate intermediate frames. • This technique provided a 75% FRR with preservation of diagnostic utility as graded by a formal reader study for cerebral angiography performed for the evaluation of cerebral vasospasm. • This approach can be applied to other types of angiography studies.

A task-driven cerebral angiographic imaging based on CT perfusion

Introduction

Current clinical computed tomography arteriography (cCTA) and clinical computed tomography venography (cCTV) images often display restricted cerebrovascular profiles, incomplete brain tissue segmentation, and incomplete artery-vein segmentation. Especially for vessels associated with diseases, capturing their complete profiles proves challenging.

Methods

In this work, we developed a Task-driven Cerebral Angiographic Imaging (TDCAI) technique using computed tomography perfusion (CTP) images of stroke patients. A evaluation on intracranial hemorrhagic stroke (IHS) and acute ischemic stroke (AIS) cases was performed with CT perfusion imaging. The TDCAI technique processed the CTP images, resulting in supplementary diagnostic images, including CTA, CTV, centerline images of the vessels-of-interest [internal carotid artery (ICA) for AIS patients, Labbé vein for IHS patients], and straightened images of the vessels-of-interest.

Results

We conducted a comparison between the obtained CTA/CTV images and the cCTA/cCTV images in terms of overall image quality and visibility of the vessels-of-interest. By constructing a virtual vascular phantom, we extracted its centerline and compared it with the actual centerline to calculate maximum and average deviations. This allowed us to evaluate both the accuracy of the centerline extraction algorithm and its capability to resist the influence of side branches. We assessed whether vascular stenosis and dilatation could be expressed in straightened vessel images, conducting statistical analyses to establish the superiority of TDCAI technique.

Discussion

This study proposes a TDCAI technique to eliminate bone and soft tissue interference, effectively segregate the comprehensive cerebral venous and arterial systems, and extract centerlines and straighten the vessels-of-interest, which would aid doctors in assessing the outflow profiles of vessels after a stroke and seeking imaging biomarkers correlated with clinical outcomes.

Endovascular Treatment of TASC C and D Femoropopliteal Arterial Disease With Heparin-Bonded Covered Stents: The Impact of Distal Run-Off Vessels

INTRODUCTION

In the last 2 decades, several studies in the literature evaluated the possible role of covered stents in the treatment of TransAtlantic Inter-Society Consensus (TASC) C and D femoropopliteal lesions but, despite the encouraging results, the employment of these devices was never included in clinical guidelines. The aim of this study is to evaluate the role of the technical aspects in patients with TASC C or D lesions that were treated with the GORE VIABAHN endoprosthesis and to elaborate a computerized method to objectively estimate the post-stent run-off and predict stent-graft failure.

MATERIALS AND METHODS

In this monocentric retrospective study, we collected the patients who were treated in our department from December 2014 to May 2021. Inclusion criteria comprised: (1) patients who underwent endovascular treatment of a TASC C or D femoropopliteal lesions using one or more heparin-bonded covered stent(s) and (2) clinical follow-up >2 years. Exclusion criteria were clinical follow-up <2 years or missing. An in-house computerized analysis to estimate the post-stent run-off, CEVERO (Computerized Estimation of VEssel Run-Off), was elaborated.

RESULTS

Sixty-six patients were enrolled in the study. Eleven patients had a TASC type C lesion, and 55 patients presented a type D lesion. The median follow-up time was 2.6 years. Twenty-nine patients (43.9%) experienced a major adverse limb event. Primary patency after 6, 12 and 24 months was 74.2%, 60.6%, and 57.6%; primary-assisted patency was 78.8%, 65.2%, and 59.1%. The presence of <2 run-off vessels (p<0.001) was correlated with stent-graft failure. The CEVERO analysis demonstrated an accuracy of 90.0% in predicting stent-graft failure.

CONCLUSIONS

The treatment of TASC C and D femoropopliteal lesions remains technically challenging. Our study supported the hypothesis that run-off is the most critical factor in determining the outcome of the procedure and that concomitant angioplasty of the tibial vessels might improve the patency of the covered stent. The CEVERO analysis could permit a real-time, objective estimation of the distal run-off using conventional angiographic images, and it might be employed as a tool in the intraprocedural decision-making process, but its clinical applicability should be evaluated on external validation cohorts.

CLINICAL IMPACT

The endovascular treatment of TASC C and D femoropopliteal lesions is technically challenging and run-off seems to be the most critical factor in determining the outcome. Concurrent angioplasty of the tibial vessels can create adequate run-off to avoid stent failure. The CEVERO analysis is a computerized estimation of run-off that might be a useful tool in the decision-making process.

Spatio-temporal physics-informed learning: A novel approach to CT perfusion analysis in acute ischemic stroke

CT perfusion imaging is important in the imaging workup of acute ischemic stroke for evaluating affected cerebral tissue. CT perfusion analysis software produces cerebral perfusion maps from commonly noisy spatio-temporal CT perfusion data. High levels of noise can influence the results of CT perfusion analysis, necessitating software tuning. This work proposes a novel approach for CT perfusion analysis that uses physics-informed learning, an optimization framework that is robust to noise. In particular, we propose SPPINN: Spatio-temporal Perfusion Physics-Informed Neural Network and research spatio-temporal physics-informed learning. SPPINN learns implicit neural representations of contrast attenuation in CT perfusion scans using the spatio-temporal coordinates of the data and employs these representations to estimate a continuous representation of the cerebral perfusion parameters. We validate the approach on simulated data to quantify perfusion parameter estimation performance. Furthermore, we apply the method to in-house patient data and the public Ischemic Stroke Lesion Segmentation 2018 benchmark data to assess the correspondence between the perfusion maps and reference standard infarct core segmentations. Our method achieves accurate perfusion parameter estimates even with high noise levels and differentiates healthy tissue from infarcted tissue. Moreover, SPPINN perfusion maps accurately correspond with reference standard infarct core segmentations. Hence, we show that using spatio-temporal physics-informed learning for cerebral perfusion estimation is accurate, even in noisy CT perfusion data. The code for this work is available at https://github.com/lucasdevries/SPPINN.

Investigating the value of radiomics stemming from DSC quantitative biomarkers in IDH mutation prediction in gliomas

Objective

This study aims to assess the value of biomarker based radiomics to predict IDH mutation in gliomas. The patient cohort consists of 160 patients histopathologicaly proven of primary glioma (WHO grades 2-4) from 3 different centers.

Methods

To quantify the DSC perfusion signal two different mathematical modeling methods were used (Gamma fitting, leakage correction algorithms) considering the assumptions about the compartments contributing in the blood flow between the extra- and intra vascular space.

Results

The Mean slope of increase (MSI) and the K1 parameter of the bidirectional exchange model exhibited the highest performance with (ACC 74.3% AUROC 74.2%) and (ACC 75% AUROC 70.5%) respectively.

Conclusion

The proposed framework on DSC-MRI radiogenomics in gliomas has the potential of becoming a reliable diagnostic support tool exploiting the mathematical modeling of the DSC signal to characterize IDH mutation status through a more reproducible and standardized signal analysis scheme for facilitating clinical translation.

Carotid Dolichoarteriopathy (Elongation) of the Carotid Arteries in Patients with Ischemic Stroke Anamnesis

Carotid artery elongation (ECA) is widespread in the asymptomatic population and among people with a history of ischemic stroke (IS). There are different points of view on the ways these changes contribute to brain ischemic damage pathogenesis. Materials and Methods: From 2019 to 2021, we included 1171 people who had suffered from IS less than one year before the investigation in the study, 404 (34.5%) women aged 27 to 95 years (64 ± 13 years) and 767 men (21-90; 60 ± 11 years). All patients involved in the study underwent multimodal radiological investigation in addition to assessments of their clinical and neurological data. Results: In this study, we were unable to detect a relationship between ECA localization and acute ischemic lesions. The frequency of ECA detection in patients with IS was the same as that in carotid and vertebral-basilar arterial systems. The prevalence of ECA was the same in patients with different IS subtypes (TOAST). There was no association between the localization of ECA and ischemic lesions; moreover, there were no differences in the IS frequency between anterior and posterior circulation. There were statistically significant decreases in linear peak systolic and end diastolic velocities in the internal carotid and vertebral arteries, as well as in the intracranial arteries in patients with ECA.

Perfusion-weighted software written in Python for DSC-MRI analysis

Introduction

Dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion studies in magnetic resonance imaging (MRI) provide valuable data for studying vascular cerebral pathophysiology in different rodent models of brain diseases (stroke, tumor grading, and neurodegenerative models). The extraction of these hemodynamic parameters via DSC-MRI is based on tracer kinetic modeling, which can be solved using deconvolution-based methods, among others. Most of the post-processing software used in preclinical studies is home-built and custom-designed. Its use being, in most cases, limited to the institution responsible for the development. In this study, we designed a tool that performs the hemodynamic quantification process quickly and in a reliable way for research purposes.

Methods

The DSC-MRI quantification tool, developed as a Python project, performs the basic mathematical steps to generate the parametric maps: cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), signal recovery (SR), and percentage signal recovery (PSR). For the validation process, a data set composed of MRI rat brain scans was evaluated: i) healthy animals, ii) temporal blood-brain barrier (BBB) dysfunction, iii) cerebral chronic hypoperfusion (CCH), iv) ischemic stroke, and v) glioblastoma multiforme (GBM) models. The resulting perfusion parameters were then compared with data retrieved from the literature.

Results

A total of 30 animals were evaluated with our DSC-MRI quantification tool. In all the models, the hemodynamic parameters reported from the literature are reproduced and they are in the same range as our results. The Bland-Altman plot used to describe the agreement between our perfusion quantitative analyses and literature data regarding healthy rats, stroke, and GBM models, determined that the agreement for CBV and MTT is higher than for CBF.

Conclusion

An open-source, Python-based DSC post-processing software package that performs key quantitative perfusion parameters has been developed. Regarding the different animal models used, the results obtained are consistent and in good agreement with the physiological patterns and values reported in the literature. Our development has been built in a modular framework to allow code customization or the addition of alternative algorithms not yet implemented.

Quantitative Analysis of Brain CT Perfusion in Healthy Beagle Dogs: A Pilot Study

Brain computed tomography (CT) perfusion is a technique that allows for the fast evaluation of cerebral hemodynamics. However, quantitative studies of brain CT perfusion in veterinary medicine are lacking. The purpose of this study was to investigate the normal range of perfusion determined via CT in brains of healthy dogs and to compare values between white matter and gray matter, differences in aging, and each hemisphere. Nine intact male beagle dogs were prospectively examined using dynamic CT scanning and post-processing for brain perfusion. Regional cerebral blood volume (rCBV), regional cerebral blood flow (rCBF), mean transit time, and time to peak were calculated. Tissue ROIs were drawn in the gray matter and white matter of the frontal, temporal, parietal, and occipital lobes; caudate nucleus; thalamus; piriform lobe; hippocampus; and cerebellum. Significant differences were observed between the white matter regions and gray matter regions for rCBV and rCBF (p < 0.05). However, no significant differences were identified between hemispheres and between young and old groups in brain regions. The findings obtained in this study involving healthy beagle dogs might serve as a reference for regional CT perfusion values in specific brain regions. These results may aid in the characterization of various brain diseases in dogs.

Accuracy of Four Different CT Perfusion Thresholds for Ischemic Core Volume and Location Estimation Using IntelliSpace Portal

Computed tomography perfusion (CTP) is frequently used in the triage of ischemic stroke patients for endovascular thrombectomy (EVT). We aimed to quantify the volumetric and spatial agreement of the CTP ischemic core estimated with different thresholds and follow-up MRI infarct volume on diffusion-weighted imaging (DWI). Patients treated with EVT between November 2017 and September 2020 with available baseline CTP and follow-up DWI were included. Data were processed with Philips IntelliSpace Portal using four different thresholds. Follow-up infarct volume was segmented on DWI. In 55 patients, the median DWI volume was 10 mL, and median estimated CTP ischemic core volumes ranged from 10-42 mL. In patients with complete reperfusion, the intraclass correlation coefficient (ICC) showed moderate-good volumetric agreement (range 0.55-0.76). A poor agreement was found for all methods in patients with successful reperfusion (ICC range 0.36-0.45). Spatial agreement (median Dice) was low for all four methods (range 0.17-0.19). Severe core overestimation was most frequently (27%) seen in Method 3 and patients with carotid-T occlusion. Our study shows moderate-good volumetric agreement between ischemic core estimates for four different thresholds and subsequent infarct volume on DWI in EVT-treated patients with complete reperfusion. The spatial agreement was similar to other commercially available software packages.

The role of automated computed topography perfusion in prediction of hemorrhagic transformation after acute ischemic stroke

INTRODUCTION

The role of computed tomography perfusion (CTP) in prediction of hemorrhagic transformation (HT) has been evolving. We aimed to study the role of automated perfusion post-processing software in prediction of HT using the commercially available RAPID software.

METHODS

Two hundred eighty-two patients with anterior circulation ischemic stroke, who underwent CTP with RAPID automated post-processing, were retrospectively enrolled and divided into HT (n = 91) and non-HT groups (n = 191). The automated RAPID-generated perfusion maps were reviewed. Mismatch volume and ratio, time to maximum (Tmax) > 4-10s volumes, hypoperfusion index, cerebral blood flow (CBF) < 20-38% volumes, cerebral blood volume (CBV) < 34%-42% volumes, and CBV index were recorded and analyzed.

RESULTS

The volumes of brain tissues suffering from reduction of cerebral blood flow (CBF < 20%-38%), reduction in cerebral blood volumes (CBV < 34-42%), and delayed contrast arrival times (Tmax > 4-10s) were significantly higher in the HT group. The mismatch volumes were also higher in the HT group (p = .001). Among these parameters, the Tmax > 6s volume was the most reliable and sensitive predictor of HT (p = .001, AUC = 0.667). However, the combination of the perfusion parameters can slightly improve the diagnostic efficiency (AUC = 0.703). There was no statistically significant difference between the non-HT group and either the parenchymal or the symptomatic subtypes.

CONCLUSION

The RAPID automated CTP parameters can provide a reliable predictor of HT overall but not the parenchymal or the symptomatic subtypes. The infarct area involving the penumbra and core represented by the Tmax > 6s threshold is the most sensitive predictor; however, the combination of the perfusion parameters can slightly improve the diagnostic efficiency.

Value of sildenafil treatment for the prevention of vasospasm‑related delayed ischemic neurological deficits and delayed brain infarction following aneurysmal subarachnoid hemorrhage

Cerebral vasospasm (CV) or delayed cerebral ischemia (DCI) constitutes the main reason for the unfavorable outcomes of patients with aneurysmal subarachnoid hemorrhage (aSAH). The present retrospective cohort study, through an evaluation with computed tomography (CT) perfusion (CTP), aimed to examine the utility of an intravenous or oral administration of sildenafil in preventing DCI that develops due to vasospasm in these patients. A retrospective cohort study was conducted, which included 34 patients in a tertiary care hospital. Of these patients, 18 were males (52.9%), and the median age was 54.4 years. Of these patients, 18 (52.9%) had undergone surgery, and 16 (47.1%) had an endovascular procedure. CTP was performed on the 3rd to the 6th day. The clinical outcome was documented at 30 days using a CT scan and a complete neurological evaluation, including the Glasgow Coma Scale assessment. There was a statistically significant difference in the number of patients who developed an ischemic event at 1 month between those who did not receive sildenafil compared to those who received sildenafil (P<0.05). In addition, the multivariate analysis revealed that cerebral blood flow was an independent factor for detecting an ischemic event in 1 month (P=0.001). On the whole, the findings of the present study indicate that the intravenous or oral administration of sildenafil may be beneficial for the prevention of DCI.

One-stop patient-specific myocardial blood flow quantification technique based on allometric scaling law

Establishing a patient-specific and non-invasive technique to derive blood flow as well as coronary structural information from one single cardiac CT imaging modality. 336 patients with chest pain or ST segment depression on electrocardiogram were retrospectively enrolled. All patients underwent adenosine-stressed dynamic CT myocardial perfusion imaging (CT-MPI) and coronary computed tomography angiography (CCTA) in sequence. Relationship between myocardial mass (M) and blood flow (Q), defined as log(Q) = b · log(M) + log(Q₀), was explored based on the general allometric scaling law. We used 267 patients to obtain the regression results and found strong linear relationship between M (gram) and Q (mL/min) (b = 0.786, log(Q₀) = 0.546, r = 0.704; p < 0.001). We Also found this correlation was applicable for patients with either normal or abnormal myocardial perfusion (p < 0.001). Datasets from the other 69 patients were used to validate this M-Q correlation and found the patient-specific blood flow could be accurately estimated from CCTA compared to that measured from CT-MPI (146.480 ± 39.607 vs 137.967 ± 36.227, r = 0.816, and 146.480 ± 39.607 vs 137.967 ± 36.227, r = 0.817, for the left ventricle region and LAD-subtended region, respectively, all unit in mL/min). In conclusion, we established a technique to provide general and patient-specific myocardial mass-blood flow correlation obeyed to allometric scaling law. Blood flow information could be directly derived from structural information acquired from CCTA.

Application of Neuroimaging for the Prediction of Hemorrhagic Transformation after Intravenous Thrombolysis in Acute Ischemic Stroke

BACKGROUND

Ischemic stroke is a common cerebrovascular disease with high morbidity, disability, and mortality worldwide. Currently, recombinant tissue plasminogen activator is the main intravenous thrombolysis agent for the treatment of acute ischemic stroke within 4.5 h after onset. Hemorrhagic transformation (HT) is the most serious complication of intravenous thrombolysis, which can significantly aggravate clinical poor prognosis. Therefore, it is important to early predict the risk of post-thrombolysis HT in patients with acute ischemic stroke.

SUMMARY

Recently, several studies have reported that neuroimaging techniques have potential value in predicting HT after intravenous thrombolysis in patients with acute ischemic stroke. The corresponding neuroimaging parameters may be effective predictors of HT after intravenous thrombolysis. In this review, we summarized and discussed the application of neuroimaging techniques and related parameters in predicting HT after intravenous thrombolysis.

KEY MESSAGES

Recognizing and understanding the predictive performance of neuroimaging parameters for HT may help assess the risk of HT after intravenous thrombolysis in patients with acute ischemic stroke and make an appropriate treatment decision.

Neural network-derived perfusion maps: A model-free approach to computed tomography perfusion in patients with acute ischemic stroke

Objective

In this study, we investigate whether a Convolutional Neural Network (CNN) can generate informative parametric maps from the pre-processed CT perfusion data in patients with acute ischemic stroke in a clinical setting.

Methods

The CNN training was performed on a subset of 100 pre-processed perfusion CT dataset, while 15 samples were kept for testing. All the data used for the training/testing of the network and for generating ground truth (GT) maps, using a state-of-the-art deconvolution algorithm, were previously pre-processed using a pipeline for motion correction and filtering. Threefold cross validation had been used to estimate the performance of the model on unseen data, reporting Mean Squared Error (MSE). Maps accuracy had been checked through manual segmentation of infarct core and total hypo-perfused regions on both CNN-derived and GT maps. Concordance among segmented lesions was assessed using the Dice Similarity Coefficient (DSC). Correlation and agreement among different perfusion analysis methods were evaluated using mean absolute volume differences, Pearson correlation coefficients, Bland-Altman analysis, and coefficient of repeatability across lesion volumes.

Results

The MSE was very low for two out of three maps, and low in the remaining map, showing good generalizability. Mean Dice scores from two different raters and the GT maps ranged from 0.80 to 0.87. Inter-rater concordance was high, and a strong correlation was found between lesion volumes of CNN maps and GT maps (0.99, 0.98, respectively).

Conclusion

The agreement between our CNN-based perfusion maps and the state-of-the-art deconvolution-algorithm perfusion analysis maps, highlights the potential of machine learning methods applied to perfusion analysis. CNN approaches can reduce the volume of data required by deconvolution algorithms to estimate the ischemic core, and thus might allow the development of novel perfusion protocols with lower radiation dose deployed to the patient.

Mechanical Thrombectomy in the Late Presentation of Anterior Circulation Large Vessel Occlusion Stroke: A Guideline From the Society of Vascular and Interventional Neurology Guidelines and Practice Standards Committee

Background and Purpose

Recent clinical trials investigating endovascular therapy (EVT) in the extended time window have opened new treatment paradigms for late-presenting patients with large vessel occlusion (LVO) stroke. The aim of this guideline is to provide up to date recommendations for the diagnosis, selection, and medical or endovascular treatment of patients with LVO presenting in the extended time window.

Methods

The Society of Vascular & Interventional Neurology (SVIN) Guidelines and Practice Clinical Standards (GAPS) committee assembled a writing group and recruited interdisciplinary experts to review and evaluate the current literature. Recommendations were assigned by the writing group using the SVIN-GAPS Class of Recommendation/Level of Evidence algorithm and SVIN GAPS guideline format. The final guideline was approved by all members of the writing group, the GAPS committee, and the SVIN board of directors.

Results

Literature review yielded three high quality randomized trials and several observational studies that have been extracted to derive the enclosed summary recommendations. In patients with LVO presenting in the 6-to-24-hour window, and with clinical imaging mismatch as defined by the DAWN and DEFUSE 3 studies, EVT is recommended. Non contrast CT can be used to evaluate infarct size as sole imaging modality for patient selection, particularly when access to CT perfusion or MRI is limited, or if their performance would incur substantial delay to treatment. In addition, several clinical questions were reviewed based on the available evidence and consensus grading.

Conclusion

These guidelines provide practical recommendations based on recent evidence on the diagnosis, selection, and treatment of patients with LVO stroke presenting in the extended time window.

Efficacy of combined intravenous plus intrathecal nimodipine administration in patients with severe cerebral vasospasm post‑aneurysmal subarachnoid hemorrhage: A retrospective cohort study

Aneurysmal subarachnoid hemorrhage (aSAH) and the ensuing cerebral vasospasm (CV) and delayed cerebral ischemia (DCI) comprise the main reasons for morbidity and mortality in affected patients. The present study aimed to evaluate the efficacy of the use of combined intravenous (IV) and intrathecal (IT) nimodipine therapy for preventing permanent neurological deterioration and DCI in patients suffering from CV post-hemorrhage. The evaluation was performed using computed tomography perfusion and transcranial doppler ultrasound. The present retrospective cohort study analyzed 14 out of 146 patients diagnosed with vasospasm due to spontaneous or aSAH. These patients were divided into two groups as follows: i) The IV group, which included patients treated with only IV nimodipine; and ii) the IV + IT group, which included patients who received IV nimodipine in combination with IT nimodipine. Of the 14 patients, 7 patients were males (50%), and the mean age was 50.9 years (SD ±19 years). In total, 6 patients [42.8%; 5 (35.7%) from group A and 1 (7.1%) from group B], who experienced clinical symptoms with severe CV, were administered intra-arterial calcium channel therapy or/and IT nimodipine following the early identification of symptomatic vasospasm. The rate of adverse ischemic events was lower with IT nimodipine management during the 1 month of follow-up (6 vs. 2 events; odds ratio, 15.00; 95% confidence interval, 1.03-218.31; P=0.031). On the whole, the findings of the present study suggest that the combined use of IT nimodipine with IV admission for patients post-aSAH who developed severe CV is a safe procedure that may prevent permanent neurological deterioration and delay unfavorable ischemic incidents.

Early diagnosis of cerebral vasospasm associated with cerebral ischemia following subarachnoid hemorrhage: Evaluation of computed tomography perfusion and transcranial doppler as accurate methods

Cerebral vasospasm (CV) constitutes a major post-operative complication and source of morbidity in cases of subarachnoid hemorrhage (SAH). The early detection of CV in SAH may be difficult both clinically and radiographically. The present pilot study thus aimed to evaluate the practicability of the technique in a tertiary healthcare setting and to assess the diagnostic effectiveness of various diagnostic computed tomography (CT) perfusion (CTP) aspects in predicting the clinical outcome of patients with SAH (traumatic and aneurysmal). A retrospective study including 34 patients in a tertiary care hospital was thus conducted. The results revealed that of the 34 patients, 18 (52.9%) were males, and the mean age was 54.4±18.5 years (16-85 years old; range, 69 years). In total, 15 (44.1%) patients had traumatic SAH following traumatic brain injury (TBI), 11 (33.3%) had aneurysmal SAH, and 8 patients (23.6%) presented with TBI without SAH as controls. CTP was performed on the third to the sixth day, and 15-20 min prior to CPT, a transcranial Doppler ultrasound was performed. Clinical outcomes were documented at 30 days using a CT scan and a complete neurological evaluation, including Glasgow Coma Scale assessment. The results of a multivariate analysis revealed that cerebral blood flow (CBF) was an independent factor for detecting an ischemic event in 1 month (P=0.003). On the whole, the present study demonstrates that CTP, and consequently CBF, is a considerable index that may identify the onset of cerebral ischemia in patients with SAH.

Basis and current state of computed tomography perfusion imaging: a review

Computed tomography perfusion (CTP) is a functional imaging that allows for providing capillary-level hemodynamics information of the desired tissue in clinics. In this paper, we aim to offer insight into CTP imaging which covers the basics and current state of CTP imaging, then summarize the technical applications in the CTP imaging as well as the future technological potential. At first, we focus on the fundamentals of CTP imaging including systematically summarized CTP image acquisition and hemodynamic parameter map estimation techniques. A short assessment is presented to outline the clinical applications with CTP imaging, and then a review of radiation dose effect of the CTP imaging on the different applications is presented. We present a categorized methodology review on known and potential solvable challenges of radiation dose reduction in CTP imaging. To evaluate the quality of CTP images, we list various standardized performance metrics. Moreover, we present a review on the determination of infarct and penumbra. Finally, we reveal the popularity and future trend of CTP imaging.

Value of pre-intervention computed tomography perfusion imaging in the assessment of tissue outcome and long-term clinical prognosis in patients with anterior circulation acute ischemic stroke receiving reperfusion therapy: a systematic review

BACKGROUND

Computed tomography perfusion (CTP) imaging has emerged as an important adjunct to the current armamentarium of acute ischemic stroke (AIS) workflow. However, its adoption in routine clinical practice is far from optimal.

PURPOSE

To investigate the putative association of CTP imaging biomarkers in the assessment of prognosis in acute ischemic stroke.

MATERIAL AND METHODS

We performed a systematic review of the literature using MEDLINE, EMBASE, and Cochrane Central Register of Clinical Trials focusing on CTP biomarkers, tissue-based and clinical-based patient outcomes. We included randomized controlled trials, prospective cohort studies, and case-controlled studies published from January 2005 to 28 August 2020. Two independent reviewers conducted the study appraisal, data extraction, and quality assessment of the studies.

RESULTS

A total of 60 full-text studies were included in the final systematic review analysis. Increasing infarct core volume is associated with reduced odds of achieving functional independence (modified Rankin score 0-2) at 90 days and is correlated with the final infarct volume when reperfusion is achieved.

CONCLUSION

CTP has value in assessing tissue perfusion status in the hyperacute stroke setting and the long-term clinical prognosis of patients with AIS receiving reperfusion therapy. However, the prognostic use of CTP requires optimization and further validation.

Noise modelling of perfusion CT images for robust hemodynamic parameter estimations

Objective. The radiation dose of cerebral perfusion computed tomography (CPCT) imaging can be reduced by lowering the milliampere-second or kilovoltage peak. However, dose reduction can decrease image quality due to excessive x-ray quanta fluctuation and reduced detector signal relative to system electronic noise, thereby influencing the accuracy of hemodynamic parameters for patients with acute stroke. Existing low-dose CPCT denoising methods, which mainly focus on specific temporal and spatial prior knowledge in low-dose CPCT images, not take the noise distribution characteristics of low-dose CPCT images into consideration. In practice, the noise of low-dose CPCT images can be much more complicated. This study first investigates the noise properties in low-dose CPCT images and proposes a perfusion deconvolution model based on the noise properties. Approach. To characterize the noise distribution in CPCT images properly, we analyze noise properties in low-dose CPCT images and find that the intra-frame noise distribution may vary in the different areas and the inter-frame noise also may vary in low-dose CPCT images. Thus, we attempt the first-ever effort to model CPCT noise with a non-independent and identical distribution (i.i.d.) mixture-of-Gaussians (MoG) model for noise assumption. Furthermore, we integrate the noise modeling strategy into a perfusion deconvolution model and present a novel perfusion deconvolution method by using self-relative structural similarity information and MoG model (named as SR-MoG) to estimate the hemodynamic parameters accurately. In the presented SR-MoG method, the self-relative structural similarity information is obtained from preprocessed low-dose CPCT images. Main results. The results show that the presented SR-MoG method can achieve promising gains over the existing deconvolution approaches. In particular, the average root-mean-square error (RMSE) of cerebral blood flow (CBF), cerebral blood volume, and mean transit time was improved by 40.3%, 69.1%, and 40.8% in the digital phantom study, and the average RMSE of CBF can be improved by 81.0% in the clinical data study, compared with tensor total variation regularization deconvolution method. Significance. The presented SR-MoG method can estimate high-accuracy hemodynamic parameters andachieve promising gains over the existing deconvolution approaches.

Predictive value of Tmax perfusion maps on final core in acute ischemic stroke: an observational single-center study

PURPOSE

To assess utility of computed tomography perfusion (CTP) protocols for selection of patients with acute ischemic stroke (AIS) for reperfusive treatments and compare the diagnostic accuracy (ACC) in predicting follow-up infarction, using time-to-maximum (Tmax) maps.

METHODS

We retrospectively reviewed consecutive AIS patients evaluated for reperfusive treatments at comprehensive stroke center, employing a multimodal computed tomography. To assess prognostic accuracy of CTP summary maps in predicting final infarct area (FIA) in AIS patients, we assumed the best correlation between non-viable tissue (NVT) and FIA in early and fully recanalized patients and/or in patients with favorable clinical response (FCR). On the other hand, the tissue at risk (TAR) should better correlate with FIA in untreated patients and in treatment failure.

RESULTS

We enrolled 158 patients, for which CTP maps with Tmax thresholds of 9.5 s and 16 s, presented sensitivity of 82.5%, specificity of 74.6%, and ACC of 75.9%. In patients selected for perfusion deficit in anterior circulation territory, CTP-Tmax > 16 s has proven relatively reliable to identify NVT in FCR patients, with a tendency to overestimate NVT. Similarly, CTP-Tmax > 9.5 s was reliable for TAR, but it was overestimated comparing to FIA, in patients with unfavorable outcomes.

CONCLUSIONS

In our experience, Tmax thresholds have proven sufficiently reliable to identify global hypoperfusion, with tendency to overestimate both NVT and TAR, not yielding satisfactory differentiation between true penumbra and benign oligoemia. In particular, the overestimation of NVT could have serious consequences in not selecting potential candidates for a reperfusion treatment.

Inferring CT perfusion parameters and uncertainties using a Bayesian approach

BACKGROUND

Computed tomography perfusion imaging is commonly used for the rapid assessment of patients presenting with symptoms of acute stroke. Maps of perfusion parameters, such as cerebral blood volume (CBV), cerebral blood flow (CBF), and mean transit time (MTT) derived from the perfusion scan data, provide crucial information for stroke diagnosis and treatment decisions. Most CT scanners use singular value decomposition (SVD)-based methods to calculate these parameters. However, some known problems are associated with conventional methods.

METHODS

In this work, we propose a Bayesian inference algorithm, which can derive both the perfusion parameters and their uncertainties. We apply the variational technique to the inference, which then becomes an expectation-maximization problem. The probability distribution (with Gaussian mean and variance) of each estimated parameter can be obtained, and the coefficient of variation is used to indicate the uncertainty. We perform evaluations using both simulations and patient studies.

RESULTS

In a simulation, we show that the proposed method has much less bias than conventional methods. Then, in separate simulations, we apply the proposed method to evaluate the impacts of various scan conditions, i.e., with different frame intervals, truncated measurement, or motion, on the parameter estimate. In one patient study, the method produced CBF and MTT maps indicating an ischemic lesion consistent with the radiologist's report. In a second patient study affected by patient movement, we showed the feasibility of applying the proposed method to motion corrected data.

CONCLUSIONS

The proposed method can be used to evaluate confidence in parameter estimation and the scan protocol design. More clinical evaluation is required to fully test the proposed method.

A Systematic Review on the Role of the Perfusion Computed Tomography in Abdominal Cancer

Background and purpose

Perfusion Computed Tomography (CTp) is an imaging technique which allows quantitative and qualitative evaluation of tissue perfusion through dynamic CT acquisitions. Since CTp is still considered a research tool in the field of abdominal imaging, the aim of this work is to provide a systematic summary of the current literature on CTp in the abdominal region to clarify the role of this technique for abdominal cancer applications.

Materials and Methods

A systematic literature search of PubMed, Web of Science, and Scopus was performed to identify original articles involving the use of CTp for clinical applications in abdominal cancer since 2011. Studies were included if they reported original data on CTp and investigated the clinical applications of CTp in abdominal cancer.

Results

Fifty-seven studies were finally included in the study. Most of the included articles (33/57) dealt with CTp at the level of the liver, while a low number of studies investigated CTp for oncologic diseases involving UGI tract (8/57), pancreas (8/57), kidneys (3/57), and colon–rectum (5/57).

Conclusions

Our study revealed that CTp could be a valuable functional imaging tool in the field of abdominal oncology, particularly as a biomarker for monitoring the response to anti-tumoral treatment.

Detection of impending perfusion deficits by intraoperative computed tomography (iCT) in aneurysm surgery of the anterior circulation

Background

The aim of our study was to evaluate the additional benefit of intraoperative computed tomography (iCT), intraoperative computed tomography angiography (iCTA), and intraoperative computed tomography perfusion (iCTP) in the intraoperative detection of impending ischemia to established methods (indocyanine green videoangiography (ICGVA), microDoppler, intraoperative neuromonitoring (IONM)) for initiating timely therapeutic measures.

Methods

Patients with primary aneurysms of the anterior circulation between October 2016 and December 2019 were included. Data of iCT modalities compared to other techniques (ICGVA, microDoppler, IONM) was recorded with emphasis on resulting operative conclusions leading to inspection of clip position, repositioning, or immediate initiation of conservative treatment strategies. Additional variables analyzed included patient demographics, aneurysm-specific characteristics, and clinical outcome.

Results

Of 194 consecutive patients, 93 patients with 100 aneurysms received iCT imaging. While IONM and ICGVA were normal, an altered vessel patency in iCTA was detected in 5 (5.4%) and a mismatch in iCTP in 7 patients (7.5%). Repositioning was considered appropriate in 2 patients (2.2%), where immediate improvement in iCTP could be documented. In a further 5 cases (5.4%), intensified conservative therapy was immediately initiated treating the reduced CBP as clip repositioning was not considered causal. In terms of clinical outcome at last FU, mRS0 was achieved in 85 (91.4%) and mRS1-2 in 7 (7.5%) and remained mRS4 in one patient with SAH (1.1%).

Conclusions

Especially iCTP can reveal signs of impending ischemia in selected cases and enable the surgeon to promptly initiate therapeutic measures such as clip repositioning or intraoperative onset of maximum conservative treatment, while established tools might fail to detect those intraoperative pathologic changes.

Value of pre-intervention CT perfusion imaging in acute ischemic stroke prognosis

Noninvasive imaging plays an important role in acute stroke towards diagnosis and ongoing management of patients. Systemic thrombolysis and endovascular thrombectomy (EVT) are proven treatments currently used in standards of care in acute stroke settings. The role of computed tomography angiography (CTA) in selecting patients with large vessel occlusion for EVT is well established. However, the value of CT perfusion (CTP) imaging in predicting outcomes after stroke remains ambiguous. This article critically evaluates the value of multimodal CT imaging in early diagnosis and prognosis of acute ischemic stroke with a focus on the role of CTP in delineating tissue characteristics, patient selection, and outcomes after reperfusion therapy. Insights on various technical and clinical considerations relevant to CTP applications in acute ischemic stroke, recommendations for existing workflow, and future areas of research are discussed.

Lung Perfusion Assessment by Bedside Electrical Impedance Tomography in Critically Ill Patients

As a portable, radiation-free imaging modality, electrical impedance tomography (EIT) technology has shown promise in the bedside visual assessment of lung perfusion distribution in critically ill patients. The two main methods of EIT for assessing lung perfusion are the pulsatility and conductivity contrast (saline) bolus method. Increasing attention is being paid to the saline bolus EIT method in the evaluation of regional pulmonary perfusion in clinical practice. This study seeks to provide an overview of experimental and clinical studies with the aim of clarifying the progress made in the use of the saline bolus EIT method. Animal studies revealed that the saline bolus EIT method presented good consistency with single-photon emission CT (SPECT) in the evaluation of lung regional perfusion changes in various pathological conditions. Moreover, the saline bolus EIT method has been applied to assess the lung perfusion in a pulmonary embolism and the effect of positive end-expiratory pressure (PEEP) on regional ventilation/perfusion ratio (V/Q) and acute respiratory distress syndrome (ARDS) in several clinical studies. The implementation of saline boluses, data analyses, precision, and cutoff values varied among different studies, and a consensus must be reached regarding the clinical application of the saline bolus EIT method. Further study is required to validate the impact of the described saline bolus EIT method on decision-making, therapeutic management, and outcomes in critically ill patients.

Improvement of automatic ischemic stroke lesion segmentation in CT perfusion maps using a learned deep neural network

Acute ischemic stroke is one of the leading causes of death and long-term disability worldwide. It occurs when a blood clot blocks an artery that supplies blood to the brain tissue. Segmentation of acute ischemic stroke lesions plays a vital role to improve diagnosis, outcome assessment, and treatment planning. The current standard approach of ischemic stroke lesion segmentation is simply thresholding the Computed Tomography Perfusion (CTP) maps, i.e., quantitative feature maps created by summarizing CTP time sequence scans. However, this approach is not precise enough (its Dice similarity score is only around 50%) to be used in practice. Numerous machine learning-based techniques have recently been proposed to improve the accuracy of ischemic stroke lesion segmentation. Although they have achieved remarkable results, they still need to be improved before they can be used in actual practice. This paper presents a novel deep learning-based technique, MutiRes U-Net, for the segmentation of ischemic stroke lesions in CTP maps. MultiRes U-Net is a modified version of the original U-Net that is re-designed to be robust to segment the objects in different scales and unusual appearances. Additionally, in this paper, we propose to enrich the input CTP maps by using their contra-lateral and corresponding Tmax images. We evaluated the proposed method using the ISLES challenge 2018 dataset. As compared to the state-of-the-art methods, the results show an improvement in segmentation task accuracy. The dice similarity score (DSC) was 68%, the Jaccard score was 57.13%, and the mean absolute volume error was 22.62(ml).

Comparative Study of Multi-Delay Pseudo-Continuous Arterial Spin Labeling Perfusion MRI and CT Perfusion in Ischemic Stroke Disease

With the aging population, stroke has gradually become the leading cause of death and disability among adults. It is necessary to verify whether multi-delay pseudo-continuous arterial spin labeling (pCASL) MRI can be used as a standard neuroimaging protocol in the patients with ischemic stroke. We aimed to investigate the clinical utility of multi-delay pCASL for evaluating cerebral perfusion in ischemic stroke disease. Twenty-one ischemic stroke patients [18 men and 3 women; median age, 62 years (age range, 37-84 years)] were enrolled in this study. All patients underwent examinations, including the multi-delay pCASL protocol (using 6 PLDs between 1,000 and 3,500 ms) and computed tomography perfusion (CTP). The cerebral blood flow (CBF) and arterial transit time (ATT) maps were obtained by the multi-delay pCASL protocol, while CBF and mean transit time (MTT) maps were derived by CTP measurements. Based on the voxel level analysis, Pearson correlation coefficients were used to estimate the associations between the two modalities in the gray matter, white matter, and whole brain of each subject. Moderate to high positive associations between ASL-CBF and CTP-CBF were acquired by voxel-level-wise analysis in the gray matter, white matter, and whole brain of the enrolled patients (all P < 0.005), and the average Pearson correlation coefficients were 0.647, 0.585, and 0.646, respectively. Highly significant positive correlations between ASL-ATT and CTP-MTT were obtained by voxel-level-wise associations in the gray matter, white matter, and whole brain (all P < 0.005), and the average Pearson correlation coefficients were 0.787, 0.707, and 0.799, respectively. In addition, significant associations between ASL and CT perfusion were obtained in the gray, white matter and whole brain, according to the subgroup analyses of patient's age and disease stage. There is a correlation between perfusion parameters from multi-delay pCASL and CT perfusion imaging in patients with ischemic stroke. Multi-delay pCASL is radiation-free and non-invasive, and could be an alternative method to CT scans for assessing perfusion in ischemic stroke disease.

AIFNet: Automatic vascular function estimation for perfusion analysis using deep learning

Perfusion imaging is crucial in acute ischemic stroke for quantifying the salvageable penumbra and irreversibly damaged core lesions. As such, it helps clinicians to decide on the optimal reperfusion treatment. In perfusion CT imaging, deconvolution methods are used to obtain clinically interpretable perfusion parameters that allow identifying brain tissue abnormalities. Deconvolution methods require the selection of two reference vascular functions as inputs to the model: the arterial input function (AIF) and the venous output function, with the AIF as the most critical model input. When manually performed, the vascular function selection is time demanding, suffers from poor reproducibility and is subject to the professionals' experience. This leads to potentially unreliable quantification of the penumbra and core lesions and, hence, might harm the treatment decision process. In this work we automatize the perfusion analysis with AIFNet, a fully automatic and end-to-end trainable deep learning approach for estimating the vascular functions. Unlike previous methods using clustering or segmentation techniques to select vascular voxels, AIFNet is directly optimized at the vascular function estimation, which allows to better recognise the time-curve profiles. Validation on the public ISLES18 stroke database shows that AIFNet almost reaches inter-rater performance for the vascular function estimation and, subsequently, for the parameter maps and core lesion quantification obtained through deconvolution. We conclude that AIFNet has potential for clinical transfer and could be incorporated in perfusion deconvolution software.

Experimental examination of radiation doses from cardiac and liver CT perfusion in a phantom study as a function of organ, age and sex

Cardiac and liver computed tomography (CT) perfusion has not been routinely implemented in the clinic and requires high radiation doses. The purpose of this study is to examine the radiation exposure and technical settings for cardiac and liver CT perfusion scans at different CT scanners. Two cardiac and three liver CT perfusion protocols were examined with the N1 LUNGMAN phantom at three multi-slice CT scanners: a single-source (I) and second- (II) and third-generation (III) dual-source CT scanners. Radiation doses were reported for the CT dose index (CTDI_vol) and dose-length product (DLP) and a standardised DLP (DLP_10cm) for cardiac and liver perfusion. The effective dose (ED_10cm) for a standardised scan length of 10 cm was estimated using conversion factors based on the International Commission on Radiological Protection (ICRP) 110 phantoms and tissue-weighting factors from ICRP 103. The proposed total lifetime attributable risk of developing cancer was determined as a function of organ, age and sex for adults. Radiation exposure for CTDI_vol, DLP/DLP_{10 cm}and ED_{10 cm}during CT perfusion was distributed as follows: for cardiac perfusion (II) 144 mGy, 1036 mGy·cm/1440 mGy·cm and 39 mSv, and (III) 28 mGy, 295 mGy·cm/279 mGy·cm and 8 mSv; for liver perfusion (I) 225 mGy, 3360 mGy·cm/2249 mGy·cm and 54 mSv, (II) 94 mGy, 1451 mGy·cm/937 mGy·cm and 22 mSv, and (III) 74 mGy, 1096 mGy·cm/739 mGy·cm and 18 mSv. The third-generation dual-source CT scanner applied the lowest doses. Proposed total lifetime attributable risk increased with decreasing age. Even though CT perfusion is a high-dose examination, we observed that new-generation CT scanners could achieve lower doses. There is a strong impact of organ, age and sex on lifetime attributable risk. Further investigations of the feasibility of these perfusion scans are required for clinical implementation.

Automated Processing of Head CT Perfusion Imaging for Ischemic Stroke Triage: A Practical Guide to Quality Assurance and Interpretation

Recent successful trials of thrombectomy launched a shift to imaging-based patient selection for stroke intervention. Many centers have adopted CT perfusion imaging (CTP) as a routine part of stroke workflow, and the demand for emergent CTP interpretation is growing. Fully automated CTP postprocessing software that rapidly generates standardized color-coded CTP summary maps with minimal user input and with easy accessibility of the software output is increasingly being adopted. Such automated postprocessing greatly streamlines clinical workflow and CTP interpretation for radiologists and other frontline physicians. However, the straightforward interface overshadows the computational complexity of the underlying postprocessing workflow, which, if not carefully examined, predisposes the interpreting physician to diagnostic errors. Using case examples, this article aims to familiarize the general radiologist with interpreting automated CTP software data output in the context of contemporary stroke management, providing a discussion of CTP acquisition and postprocessing, a stepwise guide for CTP quality assurance and troubleshooting, and a framework for avoiding clinically significant CTP interpretative pitfalls in commonly encountered clinical scenarios. Interpreting radiologists should apply the outlined approach for quality assurance and develop a comprehensive search pattern for the identified pitfalls, to ensure accurate CTP interpretation and optimize patient selection for reperfusion.

Quantitation of multiple injection dynamic PET scans: an investigation of the benefits of pooling data from separate scans when mapping kinetics

Multiple injection dynamic positron emission tomography (PET) scanning is used in the clinical management of certain groups of patients and in medical research. The analysis of these studies can be approached in two ways: (i) separate analysis of data from individual tracer injections, or (ii), concatenate/pool data from separate injections and carry out a combined analysis. The simplicity of separate analysis has some practical appeal but may not be statistically efficient. We use a linear model framework associated with a kinetic mapping scheme to develop a simplified theoretical understanding of separate and combined analysis. The theoretical framework is explored numerically using both 1D and 2D simulation models. These studies are motivated by the breast cancer flow-metabolism mismatch studies involving15O-water (H2O) and18F-Fluorodeoxyglucose (FDG) and repeat15O-H2O injections used in brain activation investigations. Numerical results are found to be substantially in line with the simple theoretical analysis: mean square error characteristics of alternative methods are well described by factors involving the local voxel-level resolution of the imaging data, the relative activities of the individual scans and the number of separate injections involved. While voxel-level resolution has dependence on scan dose, after adjustment for this effect, the impact of a combined analysis is understood in simple terms associated with the linear model used for kinetic mapping. This is true for both data reconstructed by direct filtered backprojection or iterative maximum likelihood. The proposed analysis has potential to be applied to the emerging long axial field-of-view PET scanners.